report on the first workshop 25-27 february 2013, …...start date of project: 22.02.2013 end date...

CEDR Transnational Road Research Programme Call 2012: Road owners adapting to Climate Change funded by Denmark, Germany, Norway, the Netherlands

Climate projection data base for roads: CliPDaR

Report on the first Workshop 25-27 February 2013, Offenbach, Germany DWD headquarter

Deliverable D 1.1

The CliPDaR Consortium:

CEDR Call 2012: programme name

CEDR TRANSNATIONAL ROAD RESEARCH PROGRAMME

Call 2012

Design a guideline for a transnational

database of downscaled climate projection data for road impact models

Climate projection data base for roads: CliPDaR

Start date of project: 22.02.2013 End date of project: 23.08.2013

Author(s) of this deliverable: Christoph Matulla Central Institute of Meteorology and Geodynamics Hohe Warte 38 1190 Vienna Austria Joachim Namyslo German National Meteorological Service Frankfurter Straße 135 63067 Offenbach am Main Germany

May 2013

CEDR Call 2012: programme name

Table of contents Executive summary ................................................................................................................. i 1 Preliminary remark ......................................................................................................... 1

2 Introduction .................................................................................................................... 1

3 Infrastructure and climatic threats: databases & methods ............................................... 2

3.1 Infrastructure ........................................................................................................... 2

3.2 Meteorological threats ............................................................................................. 2

3.3 Climate Datasets ..................................................................................................... 4

3.3.1 Reference Data ................................................................................................ 4

3.3.2 Climate Projections .......................................................................................... 5

3.4 Mathematical downscaling tools .............................................................................. 7

4 Concluding remarks ..................................................................................................... 11

5 Acknowledgements ...................................................................................................... 12

6 References ................................................................................................................... 13

Annex A: Time Schedule ................................................................................................... A.1

Annex B: List of Participants .............................................................................................. A.2

Annex C: Road Map .......................................................................................................... A.3

CEDR Call 2012: CliPDaR

(i)

Executive summary

The first CliPDaR meeting was focused on gathering up the expertise of the

project partners regarding climate change datasets and downscaling methods.

Findings from the ongoing Federal joint research project KLIWAS (Impacts of climate

change on waterways and navigation - searching for options of adaptation) and the

EU-COST Action VALUE (Validating and Integrating Downscaling Methods for

Climate Change Research) as well as already progressed or finished projects of the

AdSVIS programme (Adaptation of road-traffic infrastructure to climate change) of

BASt, that have been carried out in cooperation with the DWD, were presented and

discussed. These projects are of importance to CliPDaR as their findings may serve

as a solid basis.

The workshop focused on several main points: (i) the road infrastructure, (ii)

the potential threats, (iii) the available datasets, (iv) the necessary mathematical

methods/tools and (v) questions posed by the road owners. These points were

approached in a ‘brain storming’ like way: (i) and (ii) were discussed on the basis of

the projects RIVA (Risk analysis of key goods and transit axes including seaports,

part of the mentioned above AdSVIS programme suite) and RIMAROCC (RIsk

MAnagement for ROads in a Changing Climate); (iii) and (iv) are to be ruled by

standard procedures which will be defined within CliPDaR (by using the knowledge

gained within KLIWAS and VALUE). As for (v) – one central question raised by the

road authorities addresses the alleged frequent occurrence of cold winters during the

recent past. We ventilated possible strategies to quantify this claim and to identify

regions in Europe that are affected most by these onsets of cold. Mathematical

techniques that should allow for the assessment of future probabilities of such events

were assessed too.

The configuration of guidelines that determine how climate datasets and

mathematical techniques are to be used to derive decision support is one of the

significant outputs of CliPDaR. Therefore, attention was directed towards the general

framework. Thereby the correct handling of climate model output was identified as

crucial (‘the ensemble approach’). The procedure how to present results was

elaborated in order to establish a CliPDaR standard for the road authorities that

permits a quick and easy comparison of the performance of different approaches.

Finally, the CliPDaR roadmap was fixed. The fulfilment of the targeted deliverables

and milestones (the schedule) was broken down to calendar weeks.

The potential of using the urban climate model MUKLIMO_3 (a 3-dimensional

Microscale Urban CLImate MOdel; Sievers, 1995) as an "impact model" (Früh et al.,

2011) to produce climate output along transport routes was discussed. Once

surrounding area parameters close to highways as well as meteorological data from


(ii)

nearby stations are entered into MUKLIMO_3, local climate data can be produced on

a rather fine scale. This shall be of great value concerning changing climate forcings

on roads. However, a MUKLIMO_3 exercise cannot be carried out within CliPDaR.

The idea, however, may be of value regarding future studies.


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1 Preliminary remark

Concerning the CEDR Call 2012 "Road owners adapting to Climate Change" the

Project CliPDaR ("Design guideline for a transnational database of downscaled

climate projection data for road impact models" (long title)) refers exclusively to the

objective "A.1 – Review, analysis and assessment of existing (regional) Climate

Change projections regarding transnational highway networks (TEN-T) needs".

Regarding the questions of this objective the project CliPDaR is engaged in

- Assessment of statistical/dynamical downscaling: to facilitate a proper

procedure that deals with the uncertainties of the future climate with respect to

the needs of future budgets and maintenance issues

- Assessment of ensemble simulations and climate projections as well as the

definition of a pragmatic data provision for decision making

- Assessment of return periods of e.g. cold winters or hot summers.

Because of the given short time line a provision of data is not foreseen within the

frame of this project and emphasis is given to the results from already ongoing

projects, in particular VALUE and KLIWAS, to contribute to a paper of

recommendations for the involved national road agencies. The mission of CliPDaR is

to issue a guidebook setting a standard regarding data and methods that shall serve

as a basis for pan-European traffic infrastructure risk assessments.

2 Introduction

Sound road related infrastructure is of upmost importance to the economy as well

as to people. The supply with daily goods or public health care for instance relies on

the trafficability of road networks all year long. Today about 70% of the total freight is

carried across roads and this number is expected to increase significantly in the

decades to come. The volume of traffic is estimated to grow by 85% of its current

value within the next 25 years. Aside from this enormous growth there are still other

factors to be considered in the future like changes in climate, demography, demand

and technology. All these changes will affect the road infrastructures like the

surfaces, the substructures of roads, bridges or tunnels. Such future maintenance

and reinforcement works needs to be planned far-sighted. Rutting of asphalt surfaces

or ’blow ups’ of concrete roads are safety issues. They are related to heat days

together with tropical nights, which may become more frequent in the future. Longer

and more frequent heat waves will also affect e.g. bridges and become a growing

concern. Changing precipitation patterns and displacements in the storm climate

(median and variance) may state new challenges to drainage systems and slope

support (windthrow, hail, torrents of sludge, etc.).


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The following Sections refer to the main points raised above (i to v), highlight the

available expertise and highlight the strategic steps of CliPDaR.

3 Infrastructure and climatic threats: databases & methods

3.1 Infrastructure

Bridges, tunnels, supporting structures, through constructions, slope protection

measures, road surface, drainages, pump systems, etc. are all part of the stationary

infrastructure belonging to the European road network. There are non-stationary or

temporarily stationary infrastructures too (signal lights, mobile construction supplies,

etc.), but they are not of first concern for CliPDaR. Some projects of the AdSVIS

programme have already dealt with single infrastructure elements and findings

gained there will be processed in CliPDaR. Table 1 lists infrastructure elements and

relates them to climatic phenomena that potentially harm them. Within CliPDaR there

is a Workshop to be conducted in Vienna at ZAMG (May 2013) at which Austrian and

German Road Authorities will participate and formulate their requirements. The

Workshop intends to identify road infrastructure of upmost importance and appending

climate elements that control the damaging mechanisms. The following topics will be

touched at the workshop in Vienna as well: climate change projections; the impact of

climate related events; natural hazards and their link to road elements; the spatial-

temporal resolution of the needed data; the impact models used by the road

authorities; the road related datasets; how road authorities make use of climate data;

etc.

3.2 Meteorological threats

The climatic phenomena causing damages to the road infrastructure elements

are to be identified. The extent of the phenomena varies in space (from just hectares

to ten thousands of square kilometres) over Europe and time (from hours to weeks

and there is a seasonal cycle dominating the occurrence of the climatological threats

as well as variation on longer timescales as decades for example). Sometimes the

damage is caused by just one phenomenon (e.g. hail) and sometimes it is the

coincidence of two or more events (e.g. heavy precipitation after a dry spell or high

winds after a snow fall or freeze-thaw cycles together with long lasting precipitation)

that harms road infrastructure. As already mentioned above – within CliPDaR there is

a Workshop to be carried out at the ZAMG, which will focus on road infrastructure,

climatic hazards and damage causing mechanisms. Some examples for

climatological events possibly causing damages are also given in Table 1.

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Table 1: some infrastructure elements and climatological threats causing financial and other loss.


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3.3 Climate Datasets

3.3.1 Reference Data

One of the first goals of CliPDaR is the identification of homogeneous datasets

covering large regions of Central Europe. This is a central requirement to derive

comparable adaptation measures/emergency plans all over Europe regardless of

borders between different countries.

There is a number of datasets on hand describing the present day climate. They are

different in timescale (time step – days, months, seasons – and covered period),

different in spatial scale (two or three dimensional, global, continental, regional, local)

as well as different in the climatological parameter(s) comprise. The NCEP/NCAR

Reanalysis datasets (Kalnay et al., 1996) are well established in the climate

community. They reach back to 1948 and picture climatological fields (air

temperature, precipitation, etc.) on a three dimensional grid through the atmosphere

and the oceans over the whole Earth. Related Reanalysis datasets are the ERA40

(1958–2002; Compo et al., 2011) and ERA interim (1989–2008) data (Uppala et al.,

2005; Dee et al., 2011), which extend over the globe as well. Other datasets just

focus on real observations and do not make use of weather forecast models to

assemble the data onto a three dimensional grid. As such they are often site/station

based. The HISTALP dataset (Auer et al., 2007) for instance provides homogenized

(meaning errors from e.g. gauge displacements are considered) station data for a list

of climate parameters (temperature, precipitation, pressure, hours of bright sunshine

and cloudiness) at about 200 sites within the Greater Alpine Region (GAR) in Central

Europe. HISTALP contains monthly time series across GAR that reach (at some

sites) back to 1760. Daily data at Austrian stations are collected in the so called

STARTCLIM dataset (Schöner et al., 2003) which comprises temperature and

precipitation readings at about 60 stations. Most data are available from 1960

onwards as many handwritten records referring to prior periods were destroyed

during WWII. Regarding Austria there are further data on hand. Some of them were

recently generated in other research projects. The DISTURBANCE dataset (Lexer et

al., 2013) covers the period 1980–2010. It provides data on a 4 km-grid that is in

close match with the Austrian forest inventory grid (Gabler and Schadauer, 2008)

and contains daily time series of temperature (minimum, mean, maximum),

precipitation totals, vapour pressure deficit and global radiation. For Central Europe

the HYRAS dataset (Rauthe et al., 2013) provides daily estimates of air temperature,

precipitation and global radiation on a 5-km-grid (the so called "KLIWAS-grid").The

following Table gives an overview of data on hand (reference data and climate

projections):


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data set Time period spatial resolution region

NCEP/NCAR 1948 – present e.g. 2.5 degree grid Worldwide

ERA40 1958 – 2002 e.g. 2.5 degree grid worldwide

HYRAS 1961 – 2010 5 km Central Europe

HISTALP 1760 – present Station based GAR/Central Europe

StartClim 1960 – present Station based Austria

DISTURBANCE 1980 – 2010 About 4 km Austria

KLIWAS 1960 – 2100 5 km Central Europe

Table 2: Datasets that may be potentially used within CliPDaR

3.3.2 Climate Projections

Climate change studies are based on assumptions how people may impact the

planet in the future. As it is hard to tell how mankind may evolve, guesses are made.

These are related to the energy consumption, the cultural interchange, the

demographic evolution of mankind and so on. Such scenarios picture possible future

developments corridors. In many applications it is best to consider a set of rather

distinct scenarios which can be expected to cover a broad range of possible futures.

The below Figure plus the comments are taken from the IPCC homepage

(http://www.ipcc.ch) since they are standardized products.

Figure 1: Schematic illustration of SRES

scenarios (IPCC, 2000). The four

scenario “families” are shown, very

simplistically, for illustrative purposes, as

branches of a two-dimensional tree. The

two dimensions shown indicate global

and regional scenario orientation, and

development and environmental

orientation, respectively. In reality, the

four scenarios share a space of a much

higher dimensionality given the

numerous driving forces and other

assumptions needed to define any given

scenario in a particular modelling


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approach. The schematic diagram illustrates that the scenarios build on the main

driving forces of GHG emissions. Each scenario family is based on a common

specification of some of the main driving forces.

The A1 storyline and scenario family describes a future world of very rapid

economic growth, global population that peaks in mid-century and declines

thereafter, and the rapid introduction of new and more efficient technologies. Major

underlying themes are convergence among regions, capacity building, and increased

cultural and social interactions, with a substantial reduction in regional differences in

per capita income. The A1 scenario family develops into three groups that describe

alternative directions of technological change in the energy system. The three A1

groups are distinguished by their technological emphasis: fossil intensive (A1FI),

non-fossil energy sources (A1T), or a balance across all sources (A1B). The A1B

scenario is characterized by balanced energy consumption from all energy sources.

Furthermore it is assumed that the appendant techniques improve evenly

(effectiveness, environmentally friendly). The B1 storyline and scenario family

describes a convergent world with the same global population that peaks in mid-

century and declines thereafter, as in the A1 storyline, but with rapid changes in

economic structures towards a service and information economy, with reductions in

material intensity, and the introduction of clean and resource-efficient technologies.

The emphasis is on global solutions to economic, social, and environmental

sustainability, including improved equity, but without additional climate initiatives.

These scenarios are then entered into so-called Global Climate Models (GCMs)

which are mathematical based approximations of the climate system of the Earth.

The outputs of GCMs (calculated at Climate Computing Centres, as e.g. the German

one (DKRZ), located in Hamburg) are simulated processes within the climate

systems (called ‘projections’ in contrast to (weather) predictions) which are triggered

by hypothetical evolutions of mankind (the aforementioned scenarios).

The KLIWAS dataset (A1B, see below Table 3) covers the hindcast period (from

about 1960 onward) and provides a broad range of meteorological data for Central

Europe1 at a grid of 5 km spacing for the surface as well as for several pressure

levels. There are substantial deviations from station based observations (which enter

the model chain at its beginning). However, the KLIWAS dataset provides variables

that are physically consistent among each other (e.g. no precipitation without clouds),

which is not necessarily the case for the DISTURBANCE dataset (as the generation

of data was based on interpolation strategies that are not synchronized between the

different climatological variables.

1 here: Germany and his catchment areas of the main rivers (e.g. Rhine, Danube, Elbe)


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3.4 Mathematical downscaling tools

GCM projections are to be interpreted on a continental scale (e.g. von Storch et al.

1993, Johannesson et al. 1995) meaning that a projected 2-degree increase for the

next half century over Europe does not tell what may happen in the Danube valley.

Typical findings of GCM projections indicate that the warming of the lower

troposphere (warming is found in all projections, regardless of the forcing scenario

which are pictured in Figure 1) is more pronounced at high latitudes as around the

equator and more distinct over the continents than over the oceans (see Figure 2 for

an example).

Figure 2: Increasing temperatures as simulated by the ECHAM5 GCM and forced by

the A1B emission scenario

GCM projections depend on the emission scenarios and so do the changes of

the two metres temperature. There are spatial differences too. Generally there is

more warming at high latitudes and over the continents. This pattern emerges in the

near future (2020-2050) in almost all simulations. The temporal strength (the rate of

warming) of this broad pattern depends on the emission scenario later in this century.

CliPDaR aims at answering questions related to the interplay (i) between the

current climate and road damages as well as (ii) between a possible future climate

and potential damages of road infrastructure. GCM scenarios do not meet the

requirements to address this topic area. This is mainly due to the fact that the needed

data to assess the road infrastructure have to describe the local climate along roads,

not the climate at a continental scale, which GCMs do. GCM data do not refer to the

detailed scale of local areas. The gap between the so-called ‘skilful’ scale of the

GCMs (meaning continents) and the scale needed by impact modelling (road

networks) can be closed by ‘Downscaling’ (von Storch et al. 1993). Downscaling


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cascades the information from the GCM scale down to the regional or local scale of

ecosystems, infrastructures etc. Downscaling approaches can be broadly separated

in two branches. The first one is based on regional scale physical processes within

the atmosphere and further climate components (this branch is called dynamical

downscaling). It involves Regional Climate Models (RCMs), modelling the physics of

the climate system for a limited geographic area (e.g. Central Europe), running at a

rather fine spatial resolution (of a few kilometres). The second approach (called

empirical or statistical downscaling) is based on observations on the GCM scale as

well as on the local scale and derives a relationship of the scales. This relationship

formulates the regional climate variables (e.g. temperature at a certain place in

Vienna) as a function of the large scale climate information (e.g. wind over Europe)

and is used to estimate the future local scale climate (e.g. projections of the

temperature at a certain place in Vienna) state from large scale GCM projections

(estimations of the future climate over Europe).

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Figure 3: Schematic presentation of dynamical (left) and empirical downscaling approaches


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Downscaled climate information (from the continental, European scale to the

local scale of an e.g. traffic network) is the basis to develop local scale climate

change scenarios of what may happen to the road infrastructure and the

surrounding environment. Such scenarios are in turn the basis for planning

adaptation measures to protect the traffic infrastructure against changing

climatic challenges.

Before we can estimate the consequences that climate change may exert on roads,

we must know the span within which – to our present understanding – regional

climate changes may take place. To this end, the joint research project KLIWAS uses

a multi-model 'ensemble approach', whereby as many climate projections as feasible

are created using slightly different inputs, model parameters, and model physics.

From differing socio-economic scenarios through to global and regional climate

simulations and cause-and-effect models, each computed model chain is a so-called

ensemble-member. Each ensemble member portrays a slightly different projection of

the future world. The outputs of all model chains are known as the span or span of

results; other synonyms are bandwidth or spread. This ensemble approach will be

used as a profound basis for the guidelines concerning the "handling with

uncertainties".

Therefore, a 19-member ensemble on the basis of the SRES-scenario A1B and

dynamical downscaling is used in KLIWAS (Imbery et al., 2013). Furthermore,

statistical downscaling techniques, including approved bias correction methods, are

used to provide a spatial high-resolution sub-ensemble of eight climate model

simulations for climate change impact studies (see Table 3).


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Control run / SRES scenario / reanalysis driven run

GCM RCM KLIWAS ensemble

C20 / A1B

HadCM3Q0 (HC) CLM2.4.6 (ETHZ) X

HadRM3Q0 (HC) X

HadCM3Q16 (HC) HadRM3Q16 (HC)

RCA3 (C4I)

HadCM3Q3 (HC) HadRM3Q3 (HC)

RCA3 (SMHI)

BCM2 (NERSC) RCA3 (SMHI) X

HIRHAM5 (DMI)

ECHAM5-r3 (MPI-M)

RCA3 (SMHI)

RegCM3 (ICTP) X

HIRHAM5 (DMI) X

RACMO2 (KNMI) X

REMO5.7 (MPI-M) X

ECHAM5-r2 (MPI-M) REMO5.8 (MPI-M)

CLM2.4.11 (GKSS)

ECHAM5-r1 (MPI-M) CLM2.4.11 (GKSS) X

REMO5.7 (MPI-M)

ARPEGE (CNRM) HIRHAM5 (DMI)

RM5.1 (CNRM)

ERA40

CLM2.4.6 (ETHZ) X

REMO5.7 (MPI-M) X

RM4.5 (CNRM) X

Table 3: Overview of climate simulations of (i) the years 1961-2000 for the control run (C20),

(ii) projection runs for the years 2001-2100 based on the scenario A1B and (iii) Re-Analysis

driven runs (ERA40) used in KLIWAS. The symbol X in the last column indicates the

projections that are regionalised (via a RCM) and bias-corrected (Imbery et al., 2013).

4 Concluding remarks

One of the most central points of CliPDaR (next to the international approach that

covers Central Europe) is the identification of relevant climatic indices that harm the

road infrastructure. Based on such indices recommendations regarding the

downscaling method and the datasets are to be issued. During the workshop ‘freeze-

thaw’ cycles (zero temperature crossings) and periods of ice/frost-days (max/min

temperature < 0) were discussed in some depth. It was mentioned that we are in

need of a more flexible definition than just counting the number of e.g. frost days in a

row since a one day break within a period (e.g. five frost days, one day with minimum

temperature > 0, five frost days) might be of no significance. Meaning, the climate


12

indices have to be defined by the properties of the road elements. This has to be

clarified with the Road Authorities. It was mentioned that the compilation of such

events should avoid any double counting (programming issue). Once the climatic

indices, which are of relevance to the road sector are known, they can be derived

from the KLIWAS ensemble.

Another point that was discussed refers to the 'cold winter problem': The melting ice

over the Barentsea leads a manifestation of a polar height that forces humid and cold

air masses to rush in from the northeast to the Central European region. As for the

rather stable stratified atmosphere the relatively warming (in contrast to a state of

more sea ice) does not reason a low pressure system.

The changed ice-cover affects the atmospheric circulation in a way that more

humid and cold air masses are advected from the north towards Central Europe. This

mechanism may be caused by a strengthening of the polar height (especially at its

edge over Scandinavia) and a westward displacement of the North-Sibiric low. First

attempts to explain this functioning are based on observed changes in the frequency

of planetary waves. As a result such periods that may last for some weeks occur

more often. Thus, winters (averaged over the three months December, January and

February) in northern Europe are not as warm as global warming may suggest.

Next to the aforementioned projects (e.g. KLIWAS, VALUE) the German

Adaptation Strategy (DAS), the Austrian Adaptation Strategy and the IPCC

Recommendations regarding adaptation measures will be taken into account. These

sources will be completed by the German Federal expert discussions "Climate

impacts" and "guidelines 'dealing with climate projection data'". All these documents

will be considered when preparing the CliPDaR guidelines.

The next workshop will take place at the Education and Training Centre of DWD

in Langen, Germany from 3rd to 4th April, 2013. This will be the "combined workshop"

(milestone M1.3) together with collegues from KNMI of the ROADAPT project.

5 Acknowledgements

The research within CliPDaR is carried out as part of the CEDR Transnational Road

research Programme Call 2012. The funding for the research is provided by the

national road administrations of the Netherlands, Denmark, Germany and Norway.


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6 References

Auer, I. and R. Boehm, A. Jurkovic, W. Lipa, A. Orlik, R. Potzmann, W. Schoener, M. Ungersboeck, C. Matulla, K. Briffa, P. Jones, D. Efhymiadis, M. Brunetti, T. Nanni, M. Maugeri, L. Mercalli, O. Mestre, J.-M. Moisselin, M. Begert, G. Mueller-Westermeier, V. Kveton, O. Bochnicek, P. Stastny, M. Lapin, S. Szalai, T. Szentimrey, T. Cegnar, M. Dolinar, M. Gajic-Capka, K. Zaninovic, Z. Majstorovic, E. Nieplova, 2007: HISTALP – Historical Instrumental Climatological Surface Time Series of the Greater Alpine Region, International Journal of Climatology, 27, 17-46. Compo, G.P. and J.S. Whitaker, P.D. Sardeshmukh, N. Matsui, R.J. Allan, X. Yin, B.E. Gleason, R.S. Vose, G. Rutledge, P. Bessemoulin, S. Brönnimann, M. Brunet, R.I. Crouthamel, A.N. Grant, P.Y. Groisman, P.D. Jones, M. Kruk, A.C. Kruger, G.J. Marshall, M. Maugeri, H.Y. Mok, Ø. Nordli, T.F. Ross, R.M. Trigo, X.L. Wang, S.D. Woodruff, S.J. Worley, 2011: The Twentieth Century Reanalysis Project. Quarterly J. Roy. Meteorol. Soc., 137, 1-28. DOI: 10.1002/qj.776 Free and Open Access. Dee, D. P., with 35 co-authors, 2011: The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quart. J. R. Meteorol. Soc., 137, 553-597. Früh, B. and P. Becker, T. Deutschländer, J.-D. Hessel, M. Koßmann, I. Mieskes, J. Namyslo, M. Roos, U. Sievers, T. Steigerwald, H. Turau, U. Wienert, 2011: Estimation of climate change impacts on the urban heat load using an urban climate model and regional climate projections. Journal Applied Meteorology and Climatology, Vol. 50, No. 1, S. 167-184. Gabler, K. and K. Schadauer, 2008: Methods of the Austrian Forest Inventory 2000/02: Origins, approaches, design, sampling, data models, evaluation and calculation of standard error. BFW-Berichte, Wien, (142): 121 S. Imbery, F. and S. Plagemann, J. Namyslo, 2013: Processing and Analysing an Ensemble of Climate Projections for the Joint Research Project KLIWAS. Advances in Science and Research, Vol. 10 (accepted). IPCC – Intergovernmental Panel on Climate Change, 2000: SRES – Special Report on Emissions Scenarios. IPCC Working Group III. Joannesson T. and T. Jonsson, E. Källen, E. Kaas, 1995: Climate change scenarios for the nordic countries. Clim Res 5:181–195. Kalnay, E. and M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, L. Gandin, M. Iredell, S. Saha, G. White, J. Woollen, Y. Zhu, M. Chelliah, W. Ebisuzaki, W. Higgins, J. Janowiak, K. C. Mo, C. Ropelewski, J. Wang, A. Leetmaa, R. Reynolds, R. Jenne, and D. Joseph, 1996: The NMC/NCAR 40-Year Reanalysis Project". Bull. Amer. Meteor. Soc., 77, 437-471.


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Lexer, M., C. Matulla, W. Rammer, M. Zuvela-Aloise, S. Reisenhofer, M. Olefs, M. Hofstätter, F. Pasztor 2013: Modellierung von Störungsregimen in Waldökosystemen unter Klimaänderungsbedingungen final report of an ACRP project (under review). Rauthe, M. and H. Steiner, U. Riediger, A. Mazurkiewicz, A. Gratzki, 2013: A Central European precipitation climatology – Part I: Generation and validation of a high-resolution gridded daily data set (HYRAS), Meteorologische Zeitschrift, accepted. Schöner W. and I. Auer, R. Böhm, S. Thaler, 2003: StartClim.1: Quality control and statistical characteristics of selected climate parameters on the basis of daily values in the face of Extreme Value Analysis. Central Institute of Meteorology and Geodynamics (ZAMG), Vienna. Sievers, U., 1995: Verallgemeinerung der Stromfunktionsmethode auf drei Dimensionen (Generalization of the streamfunction-vorticity method to three dimension). Meteorologische Zeitschrift, Neue Folge 3, 3–15. Uppala, S., et al., 2005: The ERA-40 re-analysis. Quart. J. R. Meteorol. Soc., 131, 2961-3012. von Storch, H. and E. Zorita, U. Cubasch, 1993: Downscaling of global climate change estimates to regional scales : an application to Iberian rainfall in wintertime. Journal of Climate 6, 1161-1171.


A.1

Annex A: Time Schedule

Project "Climate Projection Data base for Roads - CliPDaR", "Handling of regional Climate

Projections (CP) - statistical methods and interpolation techniques"

1. Workshop of DWD-ZAMG-Consortium (Milestone M1.2, based on Milestone M1.1)

Place: Offenbach (DWD-Headquarters), Germany Time: 25.02. until 27.02.2013

Time Theme

25.02.2013

10:30 - 10:45 hrs 1 Adress of welcome and short introduction of participants

10:45 - 10:50 hrs 2 time schedule of Workshop

10:50 - 11:20 hrs 3 CliPDaR - short introduction

11:20 - 15:30 hrs 4 Working bases of the Consortium -

What is already existent?

ca. 11:20-12:10 hrs 4.1 ZAMG (Austrian projects based on data of CP)

ca. 12:10-13:00 hrs 4.2 DWD (Focus: KLIWAS)

ca. 13:00-14:00 hrs Lunch break

14:00-15:30 hrs 4.3 Projects of BASt (with DWD-mentoring)

ca. 15:30-16:30 hrs 4.4 MUKLIMO_3 in CliPDaR?

26.02.2013

10:00-12:40 hrs 5 Contracts – actual status and revision

(NRA-Contract, DWD-ZAMG-Agreement)

ca. 12:40-14:00 hrs Lunch break

14:00 - 16:00 7 Statistical Analysis "hot summer/cold winter",

extrem events - Clarification of the approaches

16:00 - 18:00 hrs 6 Guideline (GL) for utilization of statistical/dynamical CP

16:00-16:30 hrs 6.1 CEDR-project RIMAROCC – introduction

ca. 16:30-17:00 hrs 6.2 Already existing guidelines for utilization of CP

(in Germany and/or Austria)

ca. 17:00-18:30 hrs 6.3 Which contents should be provided in the GL (D1.3)?

27.02.2013

09:30 – 10:45 hrs 8 Roadmap for CliPDaR

- GL, statistical analyses

- Design of further workshops

10:45 – 11:45 hrs 9 Overview of data

11:45 – 12:15 hrs 10 Short draft of WS-minutes

ca. 12:15 hrs End of the workshop


A.2

Annex B: List of Participants

Name of participant 25-02-2013 26-02-2013 27-02-2013

Thomas Deutschländer, DWD x

Tobias Fuchs, DWD x

Johann-Dirk Hessel, DWD x

Florian Imbery, DWD (KLIWAS) x

Meinolf Koßmann, DWD x

Christoph Matulla, ZAMG + VALUE x x x

Joachim Namyslo, DWD + KLIWAS x x x

Sabrina Plagemann, DWD (KLIWAS) x

Andreas Walter, DWD x x


A.3

Annex C: Road Map

No Milestones Due date

1 M1.1: collecting the available knowledge and experience on statistical and dynamical downscaling (SD/DD)

week 9 / 2013

2 M1.2: first Workshop "Handling with regional climate projections - statistical methods and interpolation techniques" (ZAMG+DWD)

25.-27.02.2013 (DWD,

Offenbach)

3 M1.3: combined meeting between DWD+ZAMG and the second consortium (KNMI+Deltares+SGI+egis)

03.-04.04.2013 (DWD, Langen)

4 M1.4: finding a common guideline for end user or fix the arguments of the different approaches

31.05.2013

5 M2.1: Finding out needs and conditions of road impact models 31.05.2013

6 M2.2: Assessment of the need to utilize ensemble climate projections for road related decision making

31.05.2013

7 M2.3: Overview on the available climate projections with regard to a coherent European use.

31.05.2013

8 M2.4: second Workshop "maintenance issues of road owners concerning climate adaptation needs" (ZAMG+DWD / National Road Agencies of Austria and Germany)

06.-08.05.2013 (ZAMG, Wien)

9 M2.5: Recommendation for the use of data sets week 26 / 2013

10 M3.1: collecting the available statistical outcomes on return periods for certain events in climate projection data and discussion of the results

week 30 / 2013

11 M3.2: establish a recommendation list for maintenance issues in an uncertain climate based on the current knowledge

week 32 / 2013

12 M3.3: composition of final report week 33 / 2013

No Deliverable Name / Report Name Due date

1 D1.1: report on the outcomes of the first Workshop (M1.2) and a detailed road map of the project

week 13 / 2013

2 D1.2: report on the outcomes of the combined meeting (M1.3) week 17 / 2013

3 D1.3: guidelines for the use of SD/DD results as input for impact models

week 26 / 2013

4 D2.1: report on the outcomes of the second Workshop (M2.4) week 22 / 2013

5 D2.2: guidelines on ensemble climate projection data week 30 / 2013

6 D3.1: guidelines for coping with relatively cold winters/hot summers (or return periods of extremes)

week 31 / 2013

7 D3.2: final report week 34 / 2013

report on the first workshop 25-27 february 2013, …...start date of project: 22.02.2013 end date...

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